167 citations · 234 across the 12 of their papers we have counts for
11 papers · 1 filter
Exploring Unsupervised Cell Recognition with Prior Self-activation Maps
Pingyi Chen, Chenglu Zhu, Zhongyi Shui +4
The success of supervised deep learning models on cell recognition tasks relies on detailed annotations. Many previous works have managed to reduce the dependency on labels. Howeve…
Masked conditional variational autoencoders for chromosome straightening
Jingxiong Li, Sunyi Zheng, Zhongyi Shui +9
Karyotyping is of importance for detecting chromosomal aberrations in human disease. However, chromosomes easily appear curved in microscopic images, which prevents cytogeneticists…
Semi-supervised Cell Recognition under Point Supervision
Zhongyi Shui, Yizhi Zhao, Sunyi Zheng +6
Cell recognition is a fundamental task in digital histopathology image analysis. Point-based cell recognition (PCR) methods normally require a vast number of annotations, which is…
PathAsst: A Generative Foundation AI Assistant Towards Artificial General Intelligence of Pathology
Yuxuan Sun, Chenglu Zhu, Sunyi Zheng +6
As advances in large language models (LLMs) and multimodal techniques continue to mature, the development of general-purpose multimodal large language models (MLLMs) has surged, of…
Task-specific Fine-tuning via Variational Information Bottleneck for Weakly-supervised Pathology Whole Slide Image Classification
Honglin Li, Chenglu Zhu, Yunlong Zhang +5
While Multiple Instance Learning (MIL) has shown promising results in digital Pathology Whole Slide Image (WSI) classification, such a paradigm still faces performance and generali…
DPA-P2PNet: Deformable Proposal-aware P2PNet for Accurate Point-based Cell Detection
Zhongyi Shui, Sunyi Zheng, Chenglu Zhu +6
Point-based cell detection (PCD), which pursues high-performance cell sensing under low-cost data annotation, has garnered increased attention in computational pathology community.…
Unsupervised Dense Nuclei Detection and Segmentation with Prior Self-activation Map For Histology Images
Pingyi Chen, Chenglu Zhu, Zhongyi Shui +4
The success of supervised deep learning models in medical image segmentation relies on detailed annotations. However, labor-intensive manual labeling is costly and inefficient, esp…
End-to-end cell recognition by point annotation
Zhongyi Shui, Shichuan Zhang, Chenglu Zhu +4
Reliable quantitative analysis of immunohistochemical staining images requires accurate and robust cell detection and classification. Recent weakly-supervised methods usually estim…
ChrSNet: Chromosome Straightening using Self-attention Guided Networks
Sunyi Zheng, Jingxiong Li, Zhongyi Shui +4
Karyotyping is an important procedure to assess the possible existence of chromosomal abnormalities. However, because of the non-rigid nature, chromosomes are usually heavily curve…
Benchmarking the Robustness of Deep Neural Networks to Common Corruptions in Digital Pathology
Yunlong Zhang, Yuxuan Sun, Honglin Li +3
When designing a diagnostic model for a clinical application, it is crucial to guarantee the robustness of the model with respect to a wide range of image corruptions. Herein, an e…
Automatic Pulmonary Nodule Detection in CT Scans Using Convolutional Neural Networks Based on Maximum Intensity Projection
Sunyi Zheng, Jiapan Guo, Xiaonan Cui +3
Accurate pulmonary nodule detection is a crucial step in lung cancer screening. Computer-aided detection (CAD) systems are not routinely used by radiologists for pulmonary nodule d…